Personalized News Recommendation Algorithm for Event Network

Abstract

In order to improve the level of personalized news recommendation efficiently and accurately, an event network-oriented personalized news recommendation algorithm is proposed. First, the event network is used to analyze, predict users’ interests and preferences, and actively push information content to meet users’ personalized needs, so as to build a personalized news recommendation model. Under the mobile Internet technology, combined with the characteristics of the Internet, through the position and title similarity of sentences in the document and other features, the combined features are formed to calculate the sentence weight. Finally, the sentences are extracted according to the weight ranking to generate the news summary, so as to realize the research on personalized news recommendation algorithm for event network. The experimental results show that the proposed algorithm has high recall and coverage, short time, good recommendation effect, and strong recommendation performance.